Is there significant difference in flower seeds harvest by applying different types of fertilizers?

Research questions complete solutions correct answers key 

“Is there significant difference in flower seeds harvest by applying different types of fertilizers?”

In my proposed research question it involves measuring a few variables. Some of the variables that could be measured is the height of plant, the number of leaves produce, and the percentage crop. If the crop is equal, then it will require the means to be measured. For this research question, the one-way ANOVA is appropriate in making the evaluation between several of the categories.

The independent variable for the research questions is the type of fertilizer. The independent variable is discrete, categorical and it is measured by the nominal scale.

The dependent variables for the research question are amount of plants, height and weight, and the also the number of leaves. The dependent variables are continuous, quantitative and are measured by the ratio scale.

The variables of the research questions allows for the statistical test. Usually with one-way ANOVA a single IV is measured. Once the data has been divided into groups, the groups cannot be changed or altered during the research. So in regards to the research questions, I cannot change the treatment for flower seeds receives. However, I can do numerous of measurements as I mentioned before.

Ho: µ1= µ2= µ3= …= µk ID with k categories

Ha: µi ≠ µk

The null hypothesis above proposes that the categories means of k samples are equal. The alternate hypothesis proposes that there would be a mean that would be significantly different from the categories means.

There are two kinds of error that are likely to occur are Type I and Type II error. The Type I error will occur when the true null hypothesis is rejected incorrectly. In this case, if I would reject true null hypothesis I would have a Type I error. The Type II error  will occur when the false null hypothesis is failed to be rejected. If I accept the false null hypothesis, then I would have a Type II error.

(Instructors guidance) good idea but let's simplify that study. Let's focus on one IV and one DV. If we have more than one DV, then we have problems that we aren't prepared to address at this point in the course (MANOVA would be needed instead of ANOVA in your case). A repeated measures (also called dependent) ANOVA would be used when we measure the SAME DV multiple times from the same participant. It appears that you are measuring different DVs from the same participant -- that would be a different type of study. This sounds a lot like an independent groups test to me -- two levels of the IV -- it sounds like we need different plants in each group. It seems like it would be pretty tricky to test two different fertilizers on the exact same plant -- it seems like we would have lots of carry-over effects. 

Dependent-Samples t Test or ANOVA Proposal

This written assignment is based on the work conducted in the “Dependent-Samples t Test or ANOVA” discussion forum. Based on this initial work, feedback received, and additional research, students should submit a basic research proposal that calls for the use of a dependent-samples t test or repeated-measures ANOVA.

The paper should be APA formatted as a research proposal, and contain approximately 990-1320 words of content. Include a title page, and a reference page that includes any resources utilized.

Please include the following in the research proposal:

1. Introduction (1-2 paragraphs)

• Present the research question of interest.
• Explain how the chosen statistical test applies to this research question.
• Provide the statistical notation and written explanations for the null and alternative hypotheses.

2. Methods (1 paragraph)

• Participants
• List how many participants will be selected.
• Identify who will be the participants and their major demographic characteristics (e.g., sex, age, etc.).
• Explain how participants will be selected for the study.

3. Procedures (1-2 paragraphs)

• Identify the variables in the study.
• Describe each variable’s scale of measurement (nominal, ordinal, interval, or ratio) and characteristics (i.e., discrete vs. continuous, qualitative vs. categorical, etc.).
• Provide an operational definition for each variable, explaining how the variables will be measured.

4. Results (2-3 paragraphs)

• Describe the statistical test that will be conducted. Be sure to include why the test was chosen and why it is appropriate for this study. Include in the discussion the necessary assumptions that should be met for the chosen test and how these will be addressed.
• Identify the information that will be obtained from the results of this test and what will be needed to draw conclusions regarding the hypotheses. Be sure to include a discussion of applicable critical and calculated values, p levels, confidence intervals, effect sizes, post-hoc tests, and/or tables.

5. Discussion (1 paragraph)

• Identify any expected biases, assumptions, or faults with the proposed study and the use of the identified statistical test.
• Explain what conclusions can and cannot be made for this study, and using this statistical test.
• Describe the practical significance or importance of the results.